An approximate quasi-Newton bundle-type method for nonsmooth optimization
From MaRDI portal
Publication:370139
DOI10.1155/2013/697474zbMath1278.90315OpenAlexW1995156712WikidataQ58916658 ScholiaQ58916658MaRDI QIDQ370139
Dan Li, Li-Ping Pang, Jie Shen
Publication date: 19 September 2013
Published in: Abstract and Applied Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2013/697474
Related Items
An ODE-like nonmonotone method for nonsmooth convex optimization ⋮ A modified scaled memoryless BFGS preconditioned conjugate gradient algorithm for nonsmooth convex optimization ⋮ Randomized smoothing variance reduction method for large-scale non-smooth convex optimization ⋮ A memory gradient method for non-smooth convex optimization
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On approximations with finite precision in bundle methods for nonsmooth optimization
- A preconditioning proximal Newton method for nondifferentiable convex optimization
- Globally convergent BFGS method for nonsmooth convex optimization
- Approximations in proximal bundle methods and decomposition of convex programs
- An SQP algorithm for extended linear-quadratic problems in stochastic programming
- A quasi-second-order proximal bundle algorithm
- A descent algorithm for nonsmooth convex optimization
- An Algorithm for Nonsmooth Convex Minimization With Errors
- A modification and an extension of Lemarechal’s algorithm for nonsmooth minimization
- Quasi-Newton Bundle-Type Methods for Nondifferentiable Convex Optimization
- The 𝒰-Lagrangian of a convex function
- A Globally and Superlinearly Convergent Algorithm for Nonsmooth Convex Minimization
- A proximal bundle method based on approximate subgradients
- Minimizing and stationary sequences of convex constrained minimization problems
